Multiple solutions, multi-site, and parameter transfer to calibrate DHSVM hydrological model

The application of hydrologic models often needs sets of input parameters related to environmental attributes which are not always available. This leads to the necessity of calibrating the input parameters. However, due to the non-linearity of the hydrologic phenomena, there may be multiple “best” solutions for the calibration. This paper proposes a method for calibrating the DHSVM hydrologic model using the concepts of multiple solutions, multi-site, and parameter transfer among catchments. Eight watersheds were calibrated, resulting in obtaining five sets of “best” parameters (clusters) for each one. Afterward, each watershed was modeled using the parameters of the other catchments in order to verify if the transfer of the calibrated parameters could promote satisfactory modeling of the streamflows. The results show that clusters calibrated for one watershed may be suitable for other catchments. Besdes, the calibrated parameters of the smaller catchments were satisfactory to simulate the streamflow of the bigger catchments. The proposed method can be useful in calibrating and extrapolating the input parameters to regions that do not have information about them

ESTATÍSTICA MULTIVARIADA APLICADA À ANÁLISE DE QUALIDADE DA ÁGUA EM DIFERENTES AMBIENTES DE MICROBACIAS HIDROGRÁFICAS

Estudos sobre o comportamento da qualidade de água são importantes, desse modo, o objetivo deste trabalho foi agrupar as águas estudadas quanto à similaridade e selecionar as características físico-químicas para explicar a variabilidade da qualidade das águas em quatro microbacias. Para tanto, foram selecionadas quatro microbacias com diferentes usos do solo: pastagem, regeneração florestal, floresta e cafezal; sob diferentes ambientes: ambientes lêntico e lótico, nascentes e águas subterrâneas. As coletas ocorreram entre fevereiro de 2014 e dezembro de 2014, sendo analisados: coliformes totais e termotolerantes; oxigênio dissolvido (OD); nitrogênio total (Nt); PO43-; turbidez; temperatura; pH; Demanda Bioquímica de Oxigênio (DBO); condutividade elétrica (CE); sólidos totais (ST); sólidos dissolvidos (SD); sólidos suspensos (SS); e os metais cálcio, magnésio e ferro. Utilizou-se técnicas de análise estatística multivariada, por meio da análise de agrupamento (AA) e análise de componentes principais (ACP). Na AA, foram formados quatro grupos distintos no período chuvoso e três no período seco. A diferença entre os ambientes foi o principal fator de influência na segregação dos grupos. A partir da ACP foram selecionadas 4 componentes principais que explicaram 73,09% da variância total dos dados. As variáveis selecionadas foram CE, turbidez, magnésio, ferro, SD, Nt, DBO, pH e coliformes termotolerantes.Palavras-chave: recursos hídricos; análise de agrupamento; componentes principais; manejo de bacias hidrográficas. MULTIVARIATE STATISTICS APPLIED TO WATER QUALITY IN DIFFERENT HYDROGRAPHIC MICROBASE ENVIRONMENTS ABSTRACT: Studies on the water quality behavior are important, so the objective of this work was to group the studied waters regarding the similarity and to select the physical-chemical characteristics to explain the variability of water quality in four micro-basins. Four micro-basins with different soil uses were selected: pasture, forest regeneration, forest and coffee; under different environments: lentic and lotic environments, springs and groundwater. The collections occurred between February 2014 and December 2014, being analyzed: total coliforms and thermotolerant; dissolved oxygen (OD); total nitrogen (Nt); PO43-; turbidity; temperature; pH; Biochemical Oxygen Demand (BOD); electrical conductivity (EC); total solids (TS); dissolved solids (SD); suspended solids (SS); and the metals calcium, magnesium and iron. Multivariate statistical analysis techniques were used, through cluster analysis (AA) and principal component analysis (PCA). In AA, four distinct groups were formed in the rainy season and three in the dry season. The difference between the environments was the main factor of influence in the segregation of the groups. From the PCA, 4 main components were selected, which explained 73.09% of the total data variance. The selected variables were CE, turbidity, magnesium, iron, SD, Nt, BOD, pH and thermotolerant coliforms.Keywords: water resources; cluster analysis; principal components; river basin management

Selecting models for the estimation of reference evapotranspiration for irrigation scheduling purposes.

Alternative models for the estimation of reference evapotranspiration (ETo) are typically assessed using traditional error metrics, such as root mean square error (RMSE), which may not be sufficient to select the best model for irrigation scheduling purposes. Thus, this study analyzes the performance of the original and calibrated Hargreaves-Samani (HS), Romanenko (ROM) and Jensen-Haise (JH) equations, initially assessed using traditional error metrics, for use in irrigation scheduling, considering the simulation of different irrigation intervals/time scales. Irrigation scheduling was simulated using meteorological data collected in Viçosa-MG and Mocambinho-MG, Brazil. The Penman-Monteith FAO-56 equation was used as benchmark. In general, the original equations did not perform well to estimate ETo, except the ROM and HS equations used at Viçosa and Mocambinho, respectively. Calibration and the increase in the time scale provided performance gains. When applied in irrigation scheduling, the calibrated HS and JH equations showed the best performances. Even with greater errors in estimating ETo, the calibrated HS equation performed similarly or better than the calibrated JH equation, as it had errors with greater potential to be canceled during the soil water balance. Finally, in addition to using error metrics, the performance of the models throughout the year should be considered in their assessment. Furthermore, simulating the application of ETo models in irrigation scheduling can provide valuable information for choosing the most suitable model

FOREST COVERAGE AND STREAMFLOW OF WATERSHEDS IN THE TROPICAL ATLANTIC RAINFOREST

ABSTRACT The present study analyzed the average and minimum streamflow behavior of 11 watersheds located in the Atlantic Forest Biome, relating them to the changes in forest cover. The average minimum flow with seven days of duration (Q7), the average annual flow (Qave), the total annual precipitation (Pa) and the percentage of forest cover (FC) for each watershed were determined. The joint correlation between the FC and the Pa with the flow for each watershed were analyzed by adjusting multiple linear regression equations. The partial correlation coefficient was also used to analyze whether the variation in the FC influenced the water flow when the effects of Pa are fixed. This study allowed us to identify significant associations between FC and Pa with Q7 or Qave in only two of the watersheds. Disregarding the effects of Pa, the increase in the FC tended to result in a reduction in the Qave, and in turn increased the Q7 in these two watersheds

Aplicação do modelo HidroBacia na microbacia do córrego Jaqueira, Espírito Santo

Hydrologic simulation of watersheds is an useful tool for the water resources management and to reduce environmental degradation in watersheds. This work evaluated the applicability of the hydrologic modeling in a small watershed using the HidroBacia model at Alegre-ES and compare the results of flow maximum (Qmáx) and surface runoff flow (LES) in watershed “outlet” with rational methods (MR) and Curve Number (MNC). The soil water infiltration process is represented by means of the Green-Ampt equation, modified by Mein and Larson (GAML) in this model. This equation needs the parameters: matric potential in the wetting front, hydraulic conductivity and soil moisture in the “field saturation”. This work assessed seventy two input combinations of parameters for equation GAML. Compared to real data (obtained at the watershed “outlet”) the Qmáx and LES with the simulated by HidroBacia and by the MR and MNC. Verify in this work seven best combinations estimated Qmáx and LES in simulations with HidroBacia. The simulated data by the MR and MNC overestimated Qmáx and LES, respectively. Therefore, for experimental condition, recommend the use of hydrological model HidroBacia to estimate both parameters the Qmáx and the LES.A modelagem hidrológica aplicada em bacias hidrográficas consiste numa das principais ferramentas para a gestão dos recursos hídricos, visando minimizar o processo de degradação ambiental. O presente trabalho objetivou avaliar a aplicabilidade do modelo hidrológico HidroBacia em uma microbacia hidrográfica de Alegre-ES, além de compará-lo com os métodos Racional (MR) e Número da Curva (MNC). O processo de infiltração de água no solo no HidroBacia, representado pela equação de Green- Ampt-Mein-Larson (GAML), foi simulado por meio de 72 diferentes combinações de parâmetros de entrada, a fim de evidenciar a de melhor desempenho. Compararam-se dados reais (obtidos no exutório da microbacia) de vazão máxima de escoamento superficial (Qmáx) e lâmina escoada (LES) com aqueles simulados pelo HidroBacia e pelos MR e MNC. Verificou-se que sete, das 72 combinações, melhor estimaram Qmáx e LES nas simulações realizadas com o HidroBacia. Os dados simulados pelo MR e MNC superestimaram a Qmáx e a LES, respectivamente

ESTIMATIVA DA PRECIPITAÇÃO NO ESPÍRITO SANTO POR INTERMÉDIO DE REGRESSÃO POLINOMIAL

A precipitação é um dos principais elementos da hidrologia, sendo uma variável de grande importância para a compreensão da dinâmica do ciclo hidrológico. Apesar da sua importância, a disponibilidade de dados hidroclimáticos é baixa. Dentre as alternativas para suprir a necessidade de informações da precipitação, a modelagem matemática é uma importante ferramenta que visa e sua estimativa. Assim, este trabalho avaliou as precipitações mensais e anuais de 110 estações pluviométricas do estado do Espírito Santo e avaliou o ajuste de modelos polinomiais de ordem 1 a 4 utilizando a longitude, latitude e altitude como variáveis explicativas para a previsão dessas precipitações. A precipitação no Espírito Santo mostrou variabilidade considerável, indicando grande influência do relevo, sendo observado também que localidades com maiores altitudes apresentaram maiores totais precipitados. A regressão polinomial de quarto grau se mostrou a mais adequada em representar as precipitações médias mensais e anual. Os ajustes foram considerados suficientes para representar as precipitações do Espírito Santo, com coeficientes de determinação superiores a 0,7 e erros percentuais absolutos médios entre 5,9% e 16,6%. Foi observada uma leve tendência dos modelos em subestimar os valores observados. De maneira geral, os meses do período seco, especialmente de maio a julho, obtiveram melhor desempenho dos modelos.Palavras-chave: modelagem matemática, climatologia, hidrologia, chuva. ESTIMATION OF PRECIPITATION IN THE ESPÍRITO SANTO STATE BY POLYNOMIAL REGRESSION ABSTRACT: Precipitation is one of the main elements of hydrology, being a variable of great importance for understanding the dynamics of the hydrological cycle. Despite their importance, the availability of hydroclimatic data is low. Among the alternatives to meet the need for precipitation information, mathematical modeling is an important tool that aims its estimate. This work evaluated the monthly and annual rainfall of 110 rainfall gauges in the state of Espírito Santo and evaluated the adjustment of polynomial models of order 1 to 4 using longitude, latitude and altitude as explanatory variables to predict these precipitations. Precipitation in Espírito Santo showed considerable variability, indicating great influence of the relief, being observed that location with higher altitudes presented higher precipitated totals. The fourth-degree polynomial regression proved to be the most adequate to represent the mean monthly and annual precipitations. The adjustments were considered sufficient to represent the Espírito Santo precipitation, with coefficients of determination higher than 0.7 and mean absolute percentage errors between 5.9% and 16.6%. A slight trend of the models was observed in underestimating the observed values. In general, the months of the dry period, especially from May to July, obtained better performance of the models.Keywords: mathematical modeling, climatology, hydrology, rainfall

ESTIMATIVA DA PRECIPITAÇÃO NO ESPÍRITO SANTO POR INTERMÉDIO DE REGRESSÃO POLINOMIAL

A precipitação é um dos principais elementos da hidrologia, sendo uma variável de grande importância para a compreensão da dinâmica do ciclo hidrológico. Apesar da sua importância, a disponibilidade de dados hidroclimáticos é baixa. Dentre as alternativas para suprir a necessidade de informações da precipitação, a modelagem matemática é uma importante ferramenta que visa e sua estimativa. Assim, este trabalho avaliou as precipitações mensais e anuais de 110 estações pluviométricas do estado do Espírito Santo e avaliou o ajuste de modelos polinomiais de ordem 1 a 4 utilizando a longitude, latitude e altitude como variáveis explicativas para a previsão dessas precipitações. A precipitação no Espírito Santo mostrou variabilidade considerável, indicando grande influência do relevo, sendo observado também que localidades com maiores altitudes apresentaram maiores totais precipitados. A regressão polinomial de quarto grau se mostrou a mais adequada em representar as precipitações médias mensais e anual. Os ajustes foram considerados suficientes para representar as precipitações do Espírito Santo, com coeficientes de determinação superiores a 0,7 e erros percentuais absolutos médios entre 5,9% e 16,6%. Foi observada uma leve tendência dos modelos em subestimar os valores observados. De maneira geral, os meses do período seco, especialmente de maio a julho, obtiveram melhor desempenho dos modelos.Palavras-chave: modelagem matemática, climatologia, hidrologia, chuva. ESTIMATION OF PRECIPITATION IN THE ESPÍRITO SANTO STATE BY POLYNOMIAL REGRESSION ABSTRACT: Precipitation is one of the main elements of hydrology, being a variable of great importance for understanding the dynamics of the hydrological cycle. Despite their importance, the availability of hydroclimatic data is low. Among the alternatives to meet the need for precipitation information, mathematical modeling is an important tool that aims its estimate. This work evaluated the monthly and annual rainfall of 110 rainfall gauges in the state of Espírito Santo and evaluated the adjustment of polynomial models of order 1 to 4 using longitude, latitude and altitude as explanatory variables to predict these precipitations. Precipitation in Espírito Santo showed considerable variability, indicating great influence of the relief, being observed that location with higher altitudes presented higher precipitated totals. The fourth-degree polynomial regression proved to be the most adequate to represent the mean monthly and annual precipitations. The adjustments were considered sufficient to represent the Espírito Santo precipitation, with coefficients of determination higher than 0.7 and mean absolute percentage errors between 5.9% and 16.6%. A slight trend of the models was observed in underestimating the observed values. In general, the months of the dry period, especially from May to July, obtained better performance of the models.Keywords: mathematical modeling, climatology, hydrology, rainfall